Simultaneous Localization and Mapping with Particle Swarm Localization

In this article the authors present a simultaneous localization and mapping (SLAM) method based on probability distribution function matching. The algorithm randomly samples the posteriori pdf based on the reverse models of the range sensors, and then uses a simple function matching method to evaluate pose suggestions, which are proposed by a modified version of the particle swarm optimization method.

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